A nonparametric statistical method for image segmentation using information theory and curve evolution

IEEE Transactions on Image Processing

Volumn 14, Issue 10, 2005, Pages 1486-1502

  Kim, Junmo ^a   Fisher III, John W ^b   Yezzi, Anthony ^c   Çetin, Müjdat ^a,d   Willsky, Alan S ^a  

^a MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^d SABANCI UNIVERSITY   (Turkey)

Author keywords

Curve evolution; Image segmentation; Information theory; Level set methods; Nonparametric density estimation

Indexed keywords

APPROXIMATION THEORY; EVOLUTIONARY ALGORITHMS; IMAGE QUALITY; INFORMATION THEORY; INTEGRAL EQUATIONS; MATHEMATICAL MODELS; OPTIMIZATION; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; RANDOM PROCESSES; STATISTICAL METHODS;

CURVE EVOLUTION; IMAGE MODEL; IMAGE PIXEL INTENSITIES; LEVEL-SET METHODS; NONPARAMETRIC DENSITY ESTIMATION;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; IMAGE ENHANCEMENT; INFORMATION RETRIEVAL; INFORMATION SCIENCE; METHODOLOGY; SIGNAL PROCESSING; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; INFORMATION THEORY; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; SIGNAL PROCESSING, COMPUTER-ASSISTED;

EID: 27744599498     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2005.854442     Document Type: Article

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